Time series forecasting is a widely utilized technique to make predictions based on historical time-ordered data. For example, time series forecasting may be used in various industries such as supply and demand in supply chain management, sales forecast in retail industry and traffic analysis in transportation management.
Time series forecast models may use historical values (e.g., main time series data) as well as exogenous factors such as weather, holidays, promotion information, etc. The number of potential exogenous factors that could be used in a forecast model may be numerous. The selection of the most relevant exogenous factors for use in the forecast model may be desirable to enable an accurate forecast.